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Self-organised Aggregation in Swarms of Robots with Informed Robots

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11324))

Abstract

In this paper, we study a swarm of robots that has to select one aggregation site in an environment in which two sites are available. It is known in the literature that, in presence of asymmetries in the environment, robot swarms are able to perform a collective choice and aggregate in one among two possible sites, for example the largest of the two. We focus on an aggregation scenario where the environment is morphologically symmetric. The two aggregation sites are identical with only one exception: their colour. In addition, in the swarm only a proportion of robots, that we call the informed robots, possess extra information concerning on which specific site the swarm is required to aggregate. The rest of the robots are non-informed, thus they do not possess the above mentioned extra information. In simulation-based experiments we show that, if no robot in the swarm is informed, the swarm is able to break the symmetry and aggregates on one of the two sites at random. However, the introduction of a small proportion of informed robots is enough to break the symmetry: the majority of the swarm aggregates on the site preferred by the informed robot. Additionally, the swarm is also able to completely aggregate on one of the two sites when only 30% of the robots are informed, independently from the swarm size among those we considered. Finally, we analyse how the time dynamics of the aggregation process depend on the proportion of informed robots.

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References

  1. Alkilabi, M., Narayan, A., Tuci, E.: Cooperative object transport with a swarm of e-puck robots: robustness and scalability of evolved collective strategies. Swarm Intell. 11(3–4), 185–209 (2017)

    Article  Google Scholar 

  2. Bayindir, L., Şahin, E.: Modeling self-organized aggregation in swarm robotic systems. In: IEEE Swarm Intelligence Symposium, SIS 2009, pp. 88–95. IEEE (2009)

    Google Scholar 

  3. Bonani, M., et al.: The marXbot, a miniature mobile robot opening new perspectives for the collective-robotic research. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4187–4193 (2010)

    Google Scholar 

  4. Brambilla, M., Ferrante, E., Birattari, M., Dorigo, M.: Swarm robotics: a review from the swarm engineering perspective. Swarm Intell. 7(1), 1–41 (2013)

    Article  Google Scholar 

  5. Camazine, S.: Self-Organization in Biological Systems. Princeton University Press, Princeton (2003)

    MATH  Google Scholar 

  6. Cambier, N., Frémont, V., Trianni, V., Ferrante, E.: Embodied evolution of self-organised aggregation by cultural propagation. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A.L., Reina, A., Trianni, V. (eds.) ANTS 2018. LNCS, vol. 11172, pp. 351–359. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00533-7_29

    Chapter  Google Scholar 

  7. Campo, A., Garnier, S., Dédriche, O., Zekkri, M., Dorigo, M.: Self-organized discrimination of resources. PLoS ONE 6(5), e19888 (2010)

    Article  Google Scholar 

  8. Çelikkanat, H., Şahin, E.: Steering self-organized robot flocks through externally guided individuals. Neural Comput. Appl. 19(6), 849–865 (2010)

    Article  Google Scholar 

  9. Correll, N., Martinoli, A.: Modeling and designing self-organized aggregation in a swarm of miniature robots. Int. J. Robot. Res. 30(5), 615–626 (2011)

    Article  Google Scholar 

  10. Couzin, I., Krause, J., Franks, N., Levin, S.: Effective leadership and decision making in animal groups on the move. Nature 433, 513–516 (2005)

    Article  Google Scholar 

  11. Deneubourg, J., Lioni, A., Detrain, C.: Dynamics of aggregation and emergence of cooperation. Biol. Bull. 202(3), 262–267 (2002)

    Article  Google Scholar 

  12. Dorigo, M., et al.: Evolving self-organizing behaviors for a swarm-bot. Auton. Robot. 17(2), 223–245 (2004)

    Google Scholar 

  13. Ferrante, E., Turgut, A.E., Huepe, C., Stranieri, A., Pinciroli, C., Dorigo, M.: Self-organized flocking with a mobile robot swarm: a novel motion control method. Adapt. Behav. 20(6), 460–477 (2012)

    Article  Google Scholar 

  14. Ferrante, E., Turgut, A., Stranieri, A., Pinciroli, C., Birattari, M., Dorigo, M.: A self-adaptive communication strategy for flocking in stationary and non-stationary environments. Nat. Comput. 13(2), 225–245 (2014)

    Article  MathSciNet  Google Scholar 

  15. Garnier, S., et al.: The embodiment of cockroach aggregation behavior in a group of micro-robots. Artif. Life 14(4), 387–408 (2008)

    Google Scholar 

  16. Garnier, S., et al.: Aggregation behaviour as a source of collective decision in a group of cockroach-like-robots. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds.) ECAL 2005. LNCS (LNAI), vol. 3630, pp. 169–178. Springer, Heidelberg (2005). https://doi.org/10.1007/11553090_18

    Chapter  Google Scholar 

  17. Garnier, S., Gautrais, J., Asadpour, M., Jost, C., Theraulaz, G.: Self-organized aggregation triggers collective decision making in a group of cockroach-like robots. Adapt. Behav. 17(2), 109–133 (2009)

    Article  Google Scholar 

  18. Gauci, M., Chen, J., Li, W., Dodd, T., Groß, R.: Self-organized aggregation without computation. Int. J. Robot. Res. 33(8), 1145–1161 (2014)

    Article  Google Scholar 

  19. Hauert, S., Winkler, L., Zufferey, J., Floreano, D.: Ant-based swarming with positionless micro air vehicles for communication relay. Swarm Intell. 20(2–4), 167–188 (2008)

    Article  Google Scholar 

  20. Jeanson, R., Rivault, C., Deneubourg, J., Blanco, S., Fournier, R., Jost, C., Theraulaz, G.: Self-organized aggregation in cockroaches. Anim. Behav. 69(1), 169–180 (2005)

    Article  Google Scholar 

  21. Kato, S., Jones, M.: An extended family of circular distributions related to wrapped cauchy distributions via brownian motion. Bernoulli 19(1), 154–171 (2013)

    Article  MathSciNet  Google Scholar 

  22. Kolling, A., Walker, P., Chakraborty, N., Sycara, K., Lewis, M.: Human interaction with robot swarms: a survey. IEEE Trans. Hum. Mach. Syst. 46(1), 9–26 (2016). https://doi.org/10.1109/THMS.2015.2480801

    Article  Google Scholar 

  23. Montes de Oca, M., Ferrante, E., Scheidler, A., Pinciroli, C., Birattari, M., Dorigo, M.: Majority-rule opinion dynamics with differential latency: a mechanism for self-organized collective decision-making. Swarm Intell. 5(3–4), 305–327 (2011)

    Google Scholar 

  24. Pinciroli, C., et al.: ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intell. 6(4), 271–295 (2012)

    Google Scholar 

  25. Pini, G., Brutschy, A., Frison, M., Roli, A., Dorigo, M., Birattari, M.: Task partitioning in swarms of robots: an adaptive method for strategy selection. Swarm Intell. 5(3–4), 283–304 (2011)

    Article  Google Scholar 

  26. Şahin, E.: Swarm robotics: from sources of inspiration to domains of application. In: Şahin, E., Spears, W.M. (eds.) SR 2004. LNCS, vol. 3342, pp. 10–20. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-30552-1_2

    Chapter  Google Scholar 

  27. Sperati, V., Trianni, V., Nolfi, S.: Self-organised path formation in a swarm of robots. Swarm Intell. 5(2), 97–119 (2011)

    Article  Google Scholar 

  28. Tuci, E., Alkilabi, M., Akanyety, O.: Cooperative object transport in multi-robot systems: a review of the state-of-the-art. Front. Robot. AI 5, 1–15 (2018)

    Article  Google Scholar 

  29. Tuci, E., Rabérin, A.: On the design of generalist strategies for swarms of simulated robots engaged in a task-allocation scenario. Swarm Intell. 9(4), 267–290 (2015)

    Article  Google Scholar 

  30. Valentini, G., Ferrante, E., Dorigo, M.: The best-of-n problem in robot swarms: formalization, state of the art, and novel perspectives. Front. Robot. AI 4, 9 (2017). https://doi.org/10.3389/frobt.2017.00009. https://www.frontiersin.org/article/10.3389/frobt.2017.00009

    Article  Google Scholar 

  31. Valentini, G., Ferrante, E., Hamann, H., Dorigo, M.: Collective decision with 100 Kilobots: speed versus accuracy in binary discrimination problems. Auton. Agents Multi Agent Syst. 30(3), 553–580 (2016)

    Article  Google Scholar 

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Correspondence to Elio Tuci .

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Firat, Z., Ferrante, E., Cambier, N., Tuci, E. (2018). Self-organised Aggregation in Swarms of Robots with Informed Robots. In: Fagan, D., Martín-Vide, C., O'Neill, M., Vega-Rodríguez, M.A. (eds) Theory and Practice of Natural Computing. TPNC 2018. Lecture Notes in Computer Science(), vol 11324. Springer, Cham. https://doi.org/10.1007/978-3-030-04070-3_4

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  • DOI: https://doi.org/10.1007/978-3-030-04070-3_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04069-7

  • Online ISBN: 978-3-030-04070-3

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